illustrating the comprehensive zero-shot benchmark of 19 universal machine learning interatomic potentials and the dominant impact of training data composition for surface energy prediction. A ...
Machine learning potentials represent a transformative bridge between empirical force fields and fully fledged quantum-mechanical simulations, offering near ab initio accuracy at a fraction of the ...
Two-dimensional Group-III nitrides (h-BN, h-AlN, h-GaN, and h-InN) exhibit great promise for electronic and optoelectronic applications due to their hexagonal structures, thermal stability, and wide ...
Results that may be inaccessible to you are currently showing.
Hide inaccessible results